Wuhan National Laboratory for Optoelectronics

We fabricated a perovskite solar cell that uses a double layer of mesoporous TiO2 and ZrO2 as a scaffold infiltrated with perovskite and does not require a hole-conducting layer. The perovskite was produced by drop-casting a solution of PbI2, methylammonium (MA) iodide, and 5-ammoniumvaleric acid (5-AVA) iodide through a porous carbon film. The 5-AVA templating created mixed-cation perovskite (5-AVA)x(MA)1- xPbI3 crystals with lower defect concentration and better pore filling as well as more complete contact with the TiO2 scaffold, resulting in a longer exciton lifetime and a higher quantum yield for photoinduced charge separation as compared to MAPbI3. The cell achieved a certified power conversion efficiency of 12.8% and was stable for >1000 hours in ambient air under full sunlight.

This paper proposes an image dehazing model built with a convolutional neural network (CNN), called All-in-One Dehazing Network (AOD-Net). It is designed based on a re-formulated atmospheric scattering model. Instead of estimating the transmission matrix and the atmospheric light separately as most previous models did, AOD-Net directly generates the clean image through a light-weight CNN. Such a novel end-to-end design makes it easy to embed AOD-Net into other deep models, e.g., Faster R-CNN, for improving high-level tasks on hazy images. Experimental results on both synthesized and natural hazy image datasets demonstrate our superior performance than the state-of-the-art in terms of PSNR, SSIM and the subjective visual quality. Furthermore, when concatenating AOD-Net with Faster R-CNN, we witness a large improvement of the object detection performance on hazy images.

Perovskite solar cells (PSCs) have witnessed rapidly rising power conversion efficiencies, together with advances in stability and upscaling. Despite these advances, their limited stability and need to prove upscaling remain crucial hurdles on the path to commercialization. We summarize recent advances toward commercially viable PSCs and discuss challenges that remain. We expound the development of standardized protocols to distinguish intrinsic and extrinsic degradation factors in perovskites. We review accelerated aging tests in both cells and modules and discuss the prediction of lifetimes on the basis of degradation kinetics. Mature photovoltaic solutions, which have demonstrated excellent long-term stability in field applications, offer the perovskite community valuable insights into clearing the hurdles to commercialization.

Orbital angular momentum (OAM), which describes the “phase twist” (helical phase pattern) of light beams, has recently gained interest due to its potential applications in many diverse areas. Particularly promising is the use of OAM for optical communications since: (i) coaxially propagating OAM beams with different azimuthal OAM states are mutually orthogonal, (ii) inter-beam crosstalk can be minimized, and (iii) the beams can be efficiently multiplexed and demultiplexed. As a result, multiple OAM states could be used as different carriers for multiplexing and transmitting multiple data streams, thereby potentially increasing the system capacity. In this paper, we review recent progress in OAM beam generation/detection, multiplexing/demultiplexing, and its potential applications in different scenarios including free-space optical communications, fiber-optic communications, and RF communications. Technical challenges and perspectives of OAM beams are also discussed.

Language model pre-training, such as BERT, has significantly improved the performances of many natural language processing tasks. However, pre-trained language models are usually computationally expensive, so it is difficult to efficiently execute them on resourcerestricted devices. To accelerate inference and reduce model size while maintaining accuracy, we first propose a novel Transformer distillation method that is specially designed for knowledge distillation (KD) of the Transformer-based models. By leveraging this new KD method, the plenty of knowledge encoded in a large "teacher" BERT can be effectively transferred to a small "student" Tiny-BERT. Then, we introduce a new two-stage learning framework for TinyBERT, which performs Transformer distillation at both the pretraining and task-specific learning stages. This framework ensures that TinyBERT can capture the general-domain as well as the task-specific knowledge in BERT.

Development of efficient and robust electrocatalysts is critical for practical fuel cells. We report one-dimensional bunched platinum-nickel (Pt-Ni) alloy nanocages with a Pt-skin structure for the oxygen reduction reaction that display high mass activity (3.52 amperes per milligram platinum) and specific activity (5.16 milliamperes per square centimeter platinum), or nearly 17 and 14 times higher as compared with a commercial platinum on carbon (Pt/C) catalyst. The catalyst exhibits high stability with negligible activity decay after 50,000 cycles. Both the experimental results and theoretical calculations reveal the existence of fewer strongly bonded platinum-oxygen (Pt-O) sites induced by the strain and ligand effects. Moreover, the fuel cell assembled by this catalyst delivers a current density of 1.5 amperes per square centimeter at 0.6 volts and can operate steadily for at least 180 hours.

Flexible energy-storage devices are attracting increasing attention as they show unique promising advantages, such as flexibility, shape diversity, light weight, and so on; these properties enable applications in portable, flexible, and even wearable electronic devices, including soft electronic products, roll-up displays, and wearable devices. Consequently, considerable effort has been made in recent years to fulfill the requirements of future flexible energy-storage devices, and much progress has been witnessed. This review describes the most recent advances in flexible energy-storage devices, including flexible lithium-ion batteries and flexible supercapacitors. The latest successful examples in flexible lithium-ion batteries and their technological innovations and challenges are reviewed first. This is followed by a detailed overview of the recent progress in flexible supercapacitors based on carbon materials and a number of composites and flexible micro-supercapacitors. Some of the latest achievements regarding interesting integrated energy-storage systems are also reviewed. Further research direction is also proposed to surpass existing technological bottle-necks and realize idealized flexible energy-storage devices.

With the development of recent innovative applications (e.g., augment reality, self-driving, and various cognitive applications), more and more computation-intensive and data-intensive tasks are delay-sensitive. Mobile edge computing in ultra-dense network is expected as an effective solution for meeting the low latency demand. However, the distributed computing resource in edge cloud and energy dynamics in the battery of mobile device makes it challenging to offload tasks for users. In this paper, leveraging the idea of software defined network, we investigate the task offloading problem in ultra-dense network aiming to minimize the delay while saving the battery life of user's equipment. Specifically, we formulate the task offloading problem as a mixed integer non-linear program which is NP-hard. In order to solve it, we transform this optimization problem into two sub-problems, i.e., task placement sub-problem and resource allocation sub-problem. Based on the solution of the two sub-problems, we propose an efficient offloading scheme. Simulation results prove that the proposed scheme can reduce 20% of the task duration with 30% energy saving, compared with random and uniform task offloading schemes.

Incorporating passive radiative cooling structures into personal thermal management technologies could effectively defend humans against intensifying global climate change. We show that large-scale woven metafabrics can provide high emissivity (94.5%) in the atmospheric window and high reflectivity (92.4%) in the solar spectrum because of the hierarchical-morphology design of the randomly dispersed scatterers throughout the metafabric. Through scalable industrial textile manufacturing routes, our metafabrics exhibit desirable mechanical strength, waterproofness, and breathability for commercial clothing while maintaining efficient radiative cooling ability. Practical application tests demonstrated that a human body covered by our metafabric could be cooled ~4.8°C lower than one covered by commercial cotton fabric. The cost-effectiveness and high performance of our metafabrics present substantial advantages for intelligent garments, smart textiles, and passive radiative cooling applications.

Despite the exciting progress on power conversion efficiencies, the commercialization of the emerging lead (Pb) halide perovskite solar cell technology still faces significant challenges, one of which is the inclusion of toxic Pb. Searching for Pb-free perovskite solar cell absorbers is currently an attractive research direction. The approaches used for and the consequences of Pb replacement are reviewed herein. Reviews on the theoretical understanding of the electronic, optical, and defect properties of Pb and Pb-free halide perovskites and perovskite derivatives are provided, as well as the experimental results available in the literature. The theoretical understanding explains well why Pb halide perovskites exhibit superior photovoltaic properties, but Pb-free perovskites and perovskite derivatives do not.

A highly flexible solid-state supercapacitor was fabricated through a simple flame synthesis method and electrochemical deposition process based on a carbon nanoparticles/MnO(2) nanorods hybrid structure using polyvinyl alcohol/H(3)PO(4) electrolyte. Carbon fabric is used as a current collector and electrode (mechanical support), leading to a simplified, highly flexible, and lightweight architecture. The device exhibited good electrochemical performance with an energy density of 4.8 Wh/kg at a power density of 14 kW/kg, and a demonstration of a practical device is also presented, highlighting the path for its enormous potential in energy management.

Controlling the perovskite morphology and defects at the buried perovskite-substrate interface is challenging for inverted perovskite solar cells. In this work, we report an amphiphilic molecular hole transporter, (2-(4-(bis(4-methoxyphenyl)amino)phenyl)-1-cyanovinyl)phosphonic acid, that features a multifunctional cyanovinyl phosphonic acid group and forms a superwetting underlayer for perovskite deposition, which enables high-quality perovskite films with minimized defects at the buried interface. The resulting perovskite film has a photoluminescence quantum yield of 17% and a Shockley-Read-Hall lifetime of nearly 7 microseconds and achieved a certified power conversion efficiency (PCE) of 25.4% with an open-circuit voltage of 1.21 volts and a fill factor of 84.7%. In addition, 1-square centimeter cells and 10-square centimeter minimodules show PCEs of 23.4 and 22.0%, respectively. Encapsulated modules exhibited high stability under both operational and damp heat test conditions.

Flexible electronics is an emerging and promising technology for next generation of optoelectronic devices. Herein, hierarchical three-dimensional ZnCo(2)O(4) nanowire arrays/carbon cloth composites were synthesized as high performance binder-free anodes for Li-ion battery with the features of high reversible capacity of 1300-1400 mAh g(-1) and excellent cycling ability even after 160 cycles with a capacity of 1200 mAh g(-1). Highly flexible full batteries were also fabricated, exhibiting high flexibility, excellent electrical stability, and superior electrochemical performances.

Photoluminescence is a radiative recombination process of electron–hole pairs. Self-trapped excitons (STEs), occurring in a material with soft lattice and strong electron–phonon coupling, emit photons with broad spectrum and large Stokes shift. Recently, series halide perovskites with efficient STE emission have been reported and showed promise for solid-state lighting. In this Perspective, we present an overview of various photoluminescence phenomena with the emphasis on the mechanism and characteristics of emission derived from STEs. This is followed by the introduction of STE emission in hybrid halide perovskites. We then introduce all-inorganic STE emitters and focus in particular on the mechanism of STEs in double-perovskite Cs2AgInCl6 and strategies for efficiency improvement. Finally, we summarize the current photoluminescence and electroluminescence applications of STE emitters as well as the potential in luminescent solar concentrators and provide an overview of future research opportunities.

Due to the significance of hydrogen peroxide (H(2)O(2)) in biological systems and its practical applications, the development of efficient electrochemical H(2)O(2) sensors holds a special attraction for researchers. Various materials such as Prussian blue (PB), heme proteins, carbon nanotubes (CNTs) and transition metals have been applied to the construction of H(2)O(2) sensors. In this article, the electrocatalytic H(2)O(2) determinations are mainly focused on because they can provide a superior sensing performance over non-electrocatalytic ones. The synergetic effect between nanotechnology and electrochemical H(2)O(2) determination is also highlighted in various aspects. In addition, some recent progress for in vivo H(2)O(2) measurements is also presented. Finally, the future prospects for more efficient H(2)O(2) sensing are discussed.

Abstract Memristors with tunable resistance states are emerging building blocks of artificial neural networks. However, in situ learning on a large-scale multiple-layer memristor network has yet to be demonstrated because of challenges in device property engineering and circuit integration. Here we monolithically integrate hafnium oxide-based memristors with a foundry-made transistor array into a multiple-layer neural network. We experimentally demonstrate in situ learning capability and achieve competitive classification accuracy on a standard machine learning dataset, which further confirms that the training algorithm allows the network to adapt to hardware imperfections. Our simulation using the experimental parameters suggests that a larger network would further increase the classification accuracy. The memristor neural network is a promising hardware platform for artificial intelligence with high speed-energy efficiency.

A mesoscopic methylammonium lead iodide (CH₃NH₃PbI₃) perovskite/TiO₂ heterojunction solar cell is developed with low-cost carbon counter electrode (CE) and full printable process. With carbon black/spheroidal graphite CE, this mesoscopic heterojunction solar cell presents high stability and power conversion efficiency of 6.64%, which is higher than that of the flaky graphite based device and comparable to the conventional Au version.

A piezoresistive sensor based on ultralight and superelastic aerogel is reported to fabricate MXene/reduced graphene oxide (MX/rGO) hybrid 3D structures and utilize their pressure-sensitive characteristics. The MX/rGO aerogel not only combines the rGO’s large specific surface area and the MXene’s (Ti3C2Tx) high conductivity but also exhibits rich porous structure, which leads to performance better than that of single-component rGO or MXene in terms of the pressure sensor. The large nanosheets of rGO can prevent the poor oxidization of MXene by wrapping MXene inside the aerogel. More importantly, the piezoresistive sensor based on the MX/rGO aerogel shows extremely high sensitivity (22.56 kPa–1), fast response time (<200 ms), and good stability over 10 000 cycles. The piezoresistive sensor based on the MX/rGO hybrid 3D aerogel can easily capture the signal below 10 Pa, thus clearly testing the pulse of an adult at random. Based on its superior performance, it also demonstrates potential applications in measuring pressure distribution, distinguishing subtle strain, and monitoring healthy activity.

Organic semiconductors have attracted a lot of attention since the discovery of highly doped conductive polymers, due to the potential application in field-effect transistors (OFETs), light-emitting diodes (OLEDs) and photovoltaic cells (OPVs). Single crystals of organic semiconductors are particularly intriguing because they are free of grain boundaries and have long-range periodic order as well as minimal traps and defects. Hence, organic semiconductor crystals provide a powerful tool for revealing the intrinsic properties, examining the structure-property relationships, demonstrating the important factors for high performance devices and uncovering fundamental physics in organic semiconductors. This review provides a comprehensive overview of the molecular packing, morphology and charge transport features of organic semiconductor crystals, the control of crystallization for achieving high quality crystals and the device physics in the three main applications. We hope that this comprehensive summary can give a clear picture of the state-of-art status and guide future work in this area.

Driven by the increasing demand on handing microwave signals with compact device, low power consumption, high efficiency and high reliability, it is highly desired to generate, distribute, and process microwave signals using photonic integrated circuits. Silicon photonics offers a promising platform facilitating ultracompact microwave photonic signal processing assisted by silicon nanophotonic devices. In this paper, we propose, theoretically analyze and experimentally demonstrate a simple scheme to realize ultracompact rejection ratio tunable notch microwave photonic filter (MPF) based on a silicon photonic crystal (PhC) nanocavity with fixed extinction ratio. Using a conventional modulation scheme with only a single phase modulator (PM), the rejection ratio of the presented MPF can be tuned from about 10 dB to beyond 60 dB. Moreover, the central frequency tunable operation in the high rejection ratio region is also demonstrated in the experiment.